Original Article
Exploring correlation information for image compression of four-dimensional computed tomography
Abstract
Background: Nowadays four-dimensional computed tomography (4DCT) is popularly used in evaluating respiration-related organ motion for patients under radiotherapy. As consisting of multiple subsets of CT images, a larger storage space is needed for 4DCT. In this study, the correlations information within these subsets was explored and the popular video encoders were used for 4DCT image compression.
Methods: The images of 4DCT subsets were arranged in an order and put into a sequence for the input of video encoder. The effects of two ordering methods on the compression performance of video encoder were compared. One ordering method, phase-prioritized (PP) sequence, arranged 4DCT images according to their respiration phases. Another ordering method, location-prioritized (LP) sequence, arranged 4DCT images by their slice locations. Three popular video encoders were selected including one lossless compression algorithm and two lossy compression algorithms. Based on a publicly available database consisting of 82 4DCT datasets of 20 lung cancer patients, the performance of two ordering methods and three video encoders was quantitatively assessed.
Results: The highest compression ratios were 310 and 260 for LP and PP ordering methods respectively and achieved by one video encoder employing inter-frame prediction coding algorithm. The highest compression ratios for the other two video encoders employing intra-frame coding algorithms were 16 and 7. The LP ordering method showed less inter-frame variation and higher inter-frame similarity over the PP ordering method.
Conclusions: The LP ordering method would result in higher compression ratio than the PP ordering method for 4DCT image compression. The compression performance of video encoder employing inter-frame prediction coding algorithm is superior to those of video encoders employing intra-frame coding algorithms. The video encoder with inter-frame prediction coding algorithm and LP ordering method would be highly suitable for 4DCT image compression.
Methods: The images of 4DCT subsets were arranged in an order and put into a sequence for the input of video encoder. The effects of two ordering methods on the compression performance of video encoder were compared. One ordering method, phase-prioritized (PP) sequence, arranged 4DCT images according to their respiration phases. Another ordering method, location-prioritized (LP) sequence, arranged 4DCT images by their slice locations. Three popular video encoders were selected including one lossless compression algorithm and two lossy compression algorithms. Based on a publicly available database consisting of 82 4DCT datasets of 20 lung cancer patients, the performance of two ordering methods and three video encoders was quantitatively assessed.
Results: The highest compression ratios were 310 and 260 for LP and PP ordering methods respectively and achieved by one video encoder employing inter-frame prediction coding algorithm. The highest compression ratios for the other two video encoders employing intra-frame coding algorithms were 16 and 7. The LP ordering method showed less inter-frame variation and higher inter-frame similarity over the PP ordering method.
Conclusions: The LP ordering method would result in higher compression ratio than the PP ordering method for 4DCT image compression. The compression performance of video encoder employing inter-frame prediction coding algorithm is superior to those of video encoders employing intra-frame coding algorithms. The video encoder with inter-frame prediction coding algorithm and LP ordering method would be highly suitable for 4DCT image compression.
